Rheumatoid Arthritis: The Continuum of Disease and Strategies for Prediction, Early Intervention, and Prevention

J Rheumatol. 2024 Apr 1;51(4):337-349. doi: 10.3899/jrheum.2023-0334.

Abstract

Rheumatoid arthritis (RA) is known to include a pre-RA stage that can be defined as the presence of familial or genetic risk factors, biomarker abnormalities (eg, anticitrullinated protein antibodies [ACPA]), symptoms, and even abnormal imaging findings prior to the development of the onset of clinical RA with inflammatory arthritis that is apparent on physical examination. Indeed, there are multiple completed or ongoing retrospective case-control as well as prospective observational studies to identify the key biologic drivers of disease. Further, building on the predictive ability of combinations of biomarkers, symptoms, and imaging for future RA, there are multiple clinical trials completed, underway, or in development to identify approaches that may prevent, delay, or ameliorate future clinical RA in at-risk individuals. Importantly, however, although an effective preventive intervention has not yet been identified, at-risk individuals are being increasingly identified in clinical care; this presents a challenge of how to manage these individuals in clinical practice. This review will discuss the current understanding of the biology and natural history of RA development, nomenclature, and current models for prediction of future RA, as well as evaluate the current and ongoing clinical prevention trials with the overall goal to provide insights into the challenges and opportunities in the field of RA prevention. Moreover, this review will provide up-to-date options for clinical management of individuals at risk for RA.

Keywords: preclinical rheumatoid arthritis; prediction; prevention; rheumatoid arthritis.

Publication types

  • Review

MeSH terms

  • Arthritis, Rheumatoid* / diagnosis
  • Arthritis, Rheumatoid* / prevention & control
  • Autoantibodies
  • Biomarkers
  • Humans
  • Observational Studies as Topic
  • Research Design
  • Retrospective Studies

Substances

  • Autoantibodies
  • Biomarkers